Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Data augmentation using learned transformations for one-shot medical image segmentation
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1902.09383.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T23:33:33.804486Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T10:46:03.966749Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation c3800366-b597-46b6-a864-f9745ef91d8d · inbound
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning cites this paper.
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning Data augmentation using learned transformations for one-shot medical image segmentation
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T13:04:04.137155Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 51c9ea0a-f98a-41e9-8b2a-19437f405d62 · inbound
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation cites this paper.
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Data augmentation using learned transformations for one-shot medical image segmentation
Reference 153
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-14T10:46:03.971476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cc3f1d52-a8b5-43ab-9809-2df49047da57 · inbound
Tetrahedron-Net for Medical Image Registration cites this paper.
Tetrahedron-Net for Medical Image Registration Data augmentation using learned transformations for one-shot medical image segmentation
Reference 97
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T23:33:33.804486Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.